It is challenging in many ways to develop a net zero electricity grid. Adding renewable energies means more need for storage and for grid balancing. Grid-scale batteries handle these issues but their operation is not quite simple.
A battery has access to many different revenue streams, each being specific. No revenue alone is enough to make it economically viable. All revenues stacked and optimized together ensure profitability in the long run and a fast deployment.
We are developing optimization and trading algorithms that merge the battery revenue streams and ensure their sustainable development. Their deployment will form an autopilot that makes the best decisions, in real time, on the electricity markets to maximize the batteries profit and lifetime.
StackEase is a deeptech spinoff from the INRIA (French Institute for Research in Computer Science). It secured its first fundings and is enrolled with a world-class accelerator, starting this fall. Members are located in Paris, Lyon and Marseille.
Our values are innovation, customer satisfaction, merit and sustainability. The company’s purpose is to leverage Machine Learning to accelerate the energy transition.
- Understand, document and follow-up European electricity markets rules with a focus on short-term markets and ancillary services
- Derive trading mathematical models from regulatory texts
- Engage in meetings and working groups
- Source and build a feature database from relevant market signals
- Participate in designing algorithms for battery profit optimization
- Enrolled in the last year of master degree of computer science, applied mathematics or electrical engineering
- Excellent analytical skills, sense of synthesis and communication skills
- Knowledge in grid-scale storage systems, electricity markets and merit order mechanisms are a plus
- Enthusiastic, rigorous and autonomous, looking to discover entrepreneurship and the renewable energies
- Fluent in English, proficient in French
- Paid internship
- Partial home office possible